To integrate or not to integrate is the question: A quantitative study investigating employability challenge
Bibliographic record
Abstract
This is a scientific article that aims to investigate factors that influence employability (successful employment) of green card holders (skilled immigrants) in the Danish labor market. In 2007 Denmark introduced a ‘green card scheme’ under which skilled immigrants are granted a 3 year work permit to look for work relevant to their education. In 2009 a study conducted by Ramboll (Market research company) for the Danish government revealed that among green card holders in the Danish labor market 30% are successfully employed, 42% are doing odd jobs and 28% are unemployed. From a sample of 493 green card holders a survey was carried out. Odds ratios from logistic regression are used to illustrate significant factors that influence successful employment.\nConcept of ‘employability’ is used. The theoretical part then focuses on various individual employability factors (previous research done by scholars) that influence an individual’s capability in achieving successful employment.\nFindings reveal that green card holders who have European education, higher Danish language skills, invest more number of hours to learn Danish language and who belong to academic profession of IT are more likely to gain successful employment relevant to their education. In contrast according to this study having prior non- European work experience and local Danish education does not influence successful employment. Many of these significant factors are derived from previous research- employability challenges of skilled immigrants from Canada, Australia + New Zealand. This leads to the understanding that some employability challenges (obstacles) are international and affect employability of skilled immigrants in respect to Canada, Australia, New Zealand and Denmark.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".